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Maximal Standard Dose of Parenteral Iron for Hemodialysis Patients: An MRI-Based Decision Tree Learning Analysis

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  • Guy Rostoker
  • Mireille Griuncelli
  • Christelle Loridon
  • Théophile Magna
  • Philippe Janklewicz
  • Gilles Drahi
  • Hervé Dahan
  • Yves Cohen

Abstract

Background and Objectives: Iron overload used to be considered rare among hemodialysis patients after the advent of erythropoesis-stimulating agents, but recent MRI studies have challenged this view. The aim of this study, based on decision-tree learning and on MRI determination of hepatic iron content, was to identify a noxious pattern of parenteral iron administration in hemodialysis patients. Design, Setting, Participants and Measurements: We performed a prospective cross-sectional study from 31 January 2005 to 31 August 2013 in the dialysis centre of a French community-based private hospital. A cohort of 199 fit hemodialysis patients free of overt inflammation and malnutrition were treated for anemia with parenteral iron-sucrose and an erythropoesis-stimulating agent (darbepoetin), in keeping with current clinical guidelines. Patients had blinded measurements of hepatic iron stores by means of T1 and T2* contrast MRI, without gadolinium, together with CHi-squared Automatic Interaction Detection (CHAID) analysis. Results: The CHAID algorithm first split the patients according to their monthly infused iron dose, with a single cutoff of 250 mg/month. In the node comprising the 88 hemodialysis patients who received more than 250 mg/month of IV iron, 78 patients had iron overload on MRI (88.6%, 95% CI: 80% to 93%). The odds ratio for hepatic iron overload on MRI was 3.9 (95% CI: 1.81 to 8.4) with >250 mg/month of IV iron as compared to

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  • Guy Rostoker & Mireille Griuncelli & Christelle Loridon & Théophile Magna & Philippe Janklewicz & Gilles Drahi & Hervé Dahan & Yves Cohen, 2014. "Maximal Standard Dose of Parenteral Iron for Hemodialysis Patients: An MRI-Based Decision Tree Learning Analysis," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-14, December.
    • Handle: RePEc:plo:pone00:0115096
    DOI: 10.1371/journal.pone.0115096
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    Cited by:

    1. Juan A. Gómez-Pulido & José M. Gómez-Pulido & Diego Rodríguez-Puyol & María-Luz Polo-Luque & Miguel Vargas-Lombardo, 2021. "Predicting the Appearance of Hypotension during Hemodialysis Sessions Using Machine Learning Classifiers," IJERPH, MDPI, vol. 18(5), pages 1-17, February.
    2. Guy Rostoker & Mireille Griuncelli & Christelle Loridon & Théophile Magna & Gabrielle Machado & Gilles Drahi & Hervé Dahan & Philippe Janklewicz & Yves Cohen, 2015. "Reassessment of Iron Biomarkers for Prediction of Dialysis Iron Overload: An MRI Study," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-16, July.

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